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Introduction to Estimation and the Kalman Filter (KC-1) Extended Kalman Filter Navigation System Example

计算器编程代码，便于需要编程计算器的学员查询相关代码(Calculator programming code, to facilitate students in need of programming calculator related code)

说明：  利用python进行因子分析,因子分析可以进行降维!(Using Python factor analysis, factor analysis can reduce dimensionality!)

利用多元回归分析对气象站点数据进行插值运算。(The data of meteorological stations are interpolated by multiple regression analysis.)

利用Mathematica实现数值分析，包括Gauss-Seidel迭代，Jacobi迭代法，SOR法，牛顿迭代法等(Mathematica is used to realize numerical analysis, including Gauss-Seidel iteration, Jacobi iteration, SOR method, Newton iteration method, etc.)

实现最小二乘的仿真函数，有3次和9次多项式的拟合。(Realize the simulation of least squares function, has 3 times and 9 times polynomial fitting.)

用四阶龙格库塔法计算Lorenz混沌系统的时间序列(The time series of Lorenz chaotic system of fixed step size fourth-order Runge-Kutta method algorithm source code.)

说明：  关联维数求解，大组件构建，可以快速得到关联维数的值。(The value of correlation dimension can be obtained quickly by solving the correlation dimension and constructing large components.)

说明：  基于高斯赛德尔法的线性方程组解法（可消去系数矩阵病态）。基于牛顿法及改进的牛顿法实现对 非线性方程的求解。(Based Linear Equations high Sisaideer law (coefficient matrix can be eliminated morbid). Realization of nonlinear equations of Newton' s method for solving and improved Newton method is based.)

安德森的经典计算流体力学理论基础的学习用书。（英文版）(Anderson s classic theory of computational fluid dynamics-based learning book.)